| ageGroup | mean_age | se_age | N |
|---|---|---|---|
| Children | 10.4 | 0.2691 | 30 |
Adolescents 15.46 0.2488 30
| ageGroup | gender | n |
|---|---|---|
| Children | 0 | 14 |
| Children | 1 | 16 |
| Adolescents | 0 | 14 |
| Adolescents | 1 | 16 |
| Adults | 0 | 15 |
| Adults | 1 | 15 |
| race | n | prop_race |
|---|---|---|
| Asian | 22 | 0.2444 |
| Black | 10 | 0.1111 |
| Mixed Race | 24 | 0.2667 |
| Native American | 2 | 0.02222 |
| White | 32 | 0.3556 |
| hispanic | n | prop_hisp |
|---|---|---|
| 0 | 74 | 0.8222 |
| 1 | 16 | 0.1778 |
| data_type | block | freq | pa | mem | fr |
|---|---|---|---|---|---|
| behav | 1 | 89 | 90 | 90 | 90 |
| neur | 1 | 88 | 90 | 90 | NA |
| behav | 2 | 87 | 87 | 86 | 86 |
| neur | 2 | 85 | 82 | 82 | NA |
No, including quadratic age does not improve model fit.
##
## Call:
## lm(formula = IQ ~ age_scaled, data = subList)
##
## Residuals:
## Min 1Q Median 3Q Max
## -22.839 -9.665 -1.361 8.357 34.440
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 110.589 1.295 85.38 <2e-16 ***
## age_scaled -2.996 1.303 -2.30 0.0238 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 12.29 on 88 degrees of freedom
## Multiple R-squared: 0.0567, Adjusted R-squared: 0.04599
## F-statistic: 5.29 on 1 and 88 DF, p-value: 0.02381
There is a relation between age and IQ in the dataset. We will include IQ as an interacting fixed effect in all subsequent analyses to control for it.
| ageGroup | freqTrialType | N | freqAcc | sd | se | ci |
|---|---|---|---|---|---|---|
| Children | new | 1186 | 0.8272 | 0.3783 | 0.01098 | 0.02155 |
| Children | old | 2355 | 0.8896 | 0.3135 | 0.006459 | 0.01267 |
| Adolescents | new | 1332 | 0.9099 | 0.2864 | 0.007848 | 0.0154 |
| Adolescents | old | 2675 | 0.9215 | 0.269 | 0.005201 | 0.0102 |
| Adults | new | 1353 | 0.9623 | 0.1905 | 0.00518 | 0.01016 |
| Adults | old | 2732 | 0.9535 | 0.2106 | 0.004029 | 0.0079 |
| freqTrialType | N | freqAcc | sd | se | ci |
|---|---|---|---|---|---|
| new | 3871 | 0.9029 | 0.2962 | 0.00476 | 0.009333 |
| old | 7762 | 0.9231 | 0.2665 | 0.003025 | 0.005929 |
## Fitting 4 (g)lmer() models:
## [....]
## Mixed Model Anova Table (Type 3 tests, LRT-method)
##
## Model: freqAcc ~ ageScaled * IQScaled + (1 | sub)
## Data: freqDataNewItems
## Df full model: 5
## Effect df Chisq p.value
## 1 ageScaled 1 21.84 *** <.001
## 2 IQScaled 1 5.41 * .020
## 3 ageScaled:IQScaled 1 2.60 .107
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1
| freq Acc | |||
|---|---|---|---|
| Predictors | Estimates | CI | p |
| (Intercept) | 3.15 | 2.79 – 3.51 | <0.001 |
| ageScaled | 0.87 | 0.52 – 1.22 | <0.001 |
| IQScaled | 0.42 | 0.07 – 0.77 | 0.020 |
| ageScaled * IQScaled | 0.27 | -0.06 – 0.61 | 0.110 |
| Random Effects | |||
| σ2 | 3.29 | ||
| τ00 sub | 1.59 | ||
| ICC | 0.33 | ||
| N sub | 90 | ||
| Marginal R2 / Conditional R2 | 0.166 / 0.438 | ||
## Fitting 8 (g)lmer() models:
## [........]
## Mixed Model Anova Table (Type 3 tests, LRT-method)
##
## Model: freqAcc ~ appearanceCountScaled * ageScaled * IQScaled + (appearanceCountScaled |
## Model: sub)
## Data: freqDataOldItems
## Df full model: 11
## Effect df Chisq p.value
## 1 appearanceCountScaled 1 142.05 *** <.001
## 2 ageScaled 1 34.80 *** <.001
## 3 IQScaled 1 6.05 * .014
## 4 appearanceCountScaled:ageScaled 1 19.14 *** <.001
## 5 appearanceCountScaled:IQScaled 1 0.00 .949
## 6 ageScaled:IQScaled 1 0.06 .809
## 7 appearanceCountScaled:ageScaled:IQScaled 1 0.06 .805
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1
| freq Acc | |||
|---|---|---|---|
| Predictors | Estimates | CI | p |
| (Intercept) | 3.80 | 3.44 – 4.15 | <0.001 |
| appearanceCountScaled | 1.54 | 1.30 – 1.79 | <0.001 |
| ageScaled | 0.98 | 0.65 – 1.31 | <0.001 |
| IQScaled | 0.41 | 0.08 – 0.74 | 0.015 |
|
appearanceCountScaled * ageScaled |
0.47 | 0.26 – 0.68 | <0.001 |
|
appearanceCountScaled * IQScaled |
0.01 | -0.21 – 0.22 | 0.950 |
| ageScaled * IQScaled | 0.04 | -0.28 – 0.36 | 0.810 |
|
(appearanceCountScaled ageScaled) IQScaled |
-0.03 | -0.24 – 0.19 | 0.805 |
| Random Effects | |||
| σ2 | 3.29 | ||
| τ00 sub | 1.09 | ||
| τ11 sub.re1.appearanceCountScaled | 0.23 | ||
| ρ01 sub | 0.90 | ||
| ICC | 0.25 | ||
| N sub | 90 | ||
| Marginal R2 / Conditional R2 | 0.451 / 0.588 | ||
## Fitting one lmer() model. [DONE]
## Calculating p-values. [DONE]
## Mixed Model Anova Table (Type 3 tests, S-method)
##
## Model: freqTaskRT ~ (ageScaled + ageSquaredScaled) * IQScaled + (1 |
## Model: sub)
## Data: freqRTDataNewItems
## Effect df F p.value
## 1 ageScaled 1, 82.13 7.87 ** .006
## 2 ageSquaredScaled 1, 80.92 4.13 * .045
## 3 IQScaled 1, 79.15 1.79 .185
## 4 ageScaled:IQScaled 1, 79.59 4.80 * .031
## 5 ageSquaredScaled:IQScaled 1, 78.94 4.27 * .042
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1
| freq Task RT | |||
|---|---|---|---|
| Predictors | Estimates | CI | p |
| (Intercept) | 1.11 | 1.09 – 1.14 | <0.001 |
| ageScaled | -0.27 | -0.45 – -0.08 | 0.006 |
| ageSquaredScaled | 0.19 | 0.01 – 0.38 | 0.045 |
| IQScaled | -0.02 | -0.05 – 0.01 | 0.185 |
| ageScaled * IQScaled | -0.22 | -0.42 – -0.02 | 0.031 |
|
ageSquaredScaled * IQScaled |
0.20 | 0.01 – 0.39 | 0.042 |
| Random Effects | |||
| σ2 | 0.08 | ||
| τ00 sub | 0.01 | ||
| ICC | 0.14 | ||
| N sub | 90 | ||
| Marginal R2 / Conditional R2 | 0.083 / 0.209 | ||
## Fitting one lmer() model. [DONE]
## Calculating p-values. [DONE]
## Mixed Model Anova Table (Type 3 tests, S-method)
##
## Model: freqTaskRT ~ (ageScaled + ageSquaredScaled) * IQScaled * appearanceCountScaled +
## Model: (appearanceCountScaled | sub)
## Data: freqRTDataOldItems
## Effect df F p.value
## 1 ageScaled 1, 83.93 13.39 *** <.001
## 2 ageSquaredScaled 1, 83.48 8.99 ** .004
## 3 IQScaled 1, 82.87 5.88 * .017
## 4 appearanceCountScaled 1, 74.38 291.95 *** <.001
## 5 ageScaled:IQScaled 1, 82.94 3.84 + .053
## 6 ageSquaredScaled:IQScaled 1, 82.67 3.89 + .052
## 7 ageScaled:appearanceCountScaled 1, 80.58 0.39 .535
## 8 ageSquaredScaled:appearanceCountScaled 1, 78.24 0.26 .611
## 9 IQScaled:appearanceCountScaled 1, 75.13 0.06 .807
## 10 ageScaled:IQScaled:appearanceCountScaled 1, 76.59 0.27 .606
## 11 ageSquaredScaled:IQScaled:appearanceCountScaled 1, 75.02 0.34 .559
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1
| freq Task RT | |||
|---|---|---|---|
| Predictors | Estimates | CI | p |
| (Intercept) | 1.03 | 1.00 – 1.06 | <0.001 |
| ageScaled | -0.36 | -0.55 – -0.17 | <0.001 |
| ageSquaredScaled | 0.30 | 0.10 – 0.49 | 0.004 |
| IQScaled | -0.04 | -0.06 – -0.01 | 0.017 |
| appearanceCountScaled | -0.08 | -0.09 – -0.07 | <0.001 |
| ageScaled * IQScaled | -0.21 | -0.41 – 0.00 | 0.053 |
|
ageSquaredScaled * IQScaled |
0.20 | 0.00 – 0.40 | 0.052 |
|
ageScaled * appearanceCountScaled |
-0.02 | -0.09 – 0.05 | 0.535 |
|
ageSquaredScaled * appearanceCountScaled |
0.02 | -0.05 – 0.08 | 0.611 |
|
IQScaled * appearanceCountScaled |
0.00 | -0.01 – 0.01 | 0.807 |
|
(ageScaled * IQScaled) * appearanceCountScaled |
-0.02 | -0.09 – 0.05 | 0.606 |
|
(ageSquaredScaled IQScaled) appearanceCountScaled |
0.02 | -0.05 – 0.09 | 0.559 |
| Random Effects | |||
| σ2 | 0.07 | ||
| τ00 sub | 0.02 | ||
| τ11 sub.re1.appearanceCountScaled | 0.00 | ||
| ρ01 sub | 0.36 | ||
| ICC | 0.18 | ||
| N sub | 90 | ||
| Marginal R2 / Conditional R2 | 0.150 / 0.306 | ||
| ageGroup | N | rep_error_mag | sd | se | ci |
|---|---|---|---|---|---|
| Children | 1290 | 1.457 | 1.317 | 0.03667 | 0.07194 |
| Adolescents | 1383 | 1.095 | 1.112 | 0.0299 | 0.05865 |
| Adults | 1434 | 1.124 | 1.046 | 0.02762 | 0.05418 |
## Fitting one lmer() model. [DONE]
## Calculating p-values. [DONE]
## Mixed Model Anova Table (Type 3 tests, S-method)
##
## Model: rep_error_mag ~ (ageScaled + ageSquaredScaled) * IQScaled * freqCond +
## Model: (freqCond | sub)
## Data: freqReports
## Effect df F p.value
## 1 ageScaled 1, 83.86 12.50 *** <.001
## 2 ageSquaredScaled 1, 83.50 8.73 ** .004
## 3 IQScaled 1, 84.73 10.18 ** .002
## 4 freqCond 1, 83.72 0.08 .773
## 5 ageScaled:IQScaled 1, 83.26 0.19 .667
## 6 ageSquaredScaled:IQScaled 1, 82.97 0.06 .813
## 7 ageScaled:freqCond 1, 83.91 0.04 .839
## 8 ageSquaredScaled:freqCond 1, 83.72 0.01 .917
## 9 IQScaled:freqCond 1, 84.38 0.25 .622
## 10 ageScaled:IQScaled:freqCond 1, 83.54 0.47 .495
## 11 ageSquaredScaled:IQScaled:freqCond 1, 83.39 0.28 .600
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1
| rep error mag | |||
|---|---|---|---|
| Predictors | Estimates | CI | p |
| (Intercept) | 1.20 | 1.13 – 1.28 | <0.001 |
| ageScaled | -0.98 | -1.53 – -0.44 | 0.001 |
| ageSquaredScaled | 0.81 | 0.27 – 1.35 | 0.004 |
| IQScaled | -0.13 | -0.21 – -0.05 | 0.002 |
| freqCond [1] | -0.02 | -0.13 – 0.10 | 0.773 |
| ageScaled * IQScaled | -0.13 | -0.70 – 0.45 | 0.667 |
|
ageSquaredScaled * IQScaled |
0.07 | -0.48 – 0.61 | 0.813 |
| ageScaled * freqCond [1] | -0.08 | -0.87 – 0.71 | 0.839 |
|
ageSquaredScaled * freqCond [1] |
0.04 | -0.74 – 0.83 | 0.917 |
| IQScaled * freqCond [1] | -0.03 | -0.14 – 0.09 | 0.622 |
|
(ageScaled * IQScaled) * freqCond [1] |
-0.29 | -1.12 – 0.54 | 0.495 |
|
(ageSquaredScaled IQScaled) freqCond [1] |
0.21 | -0.58 – 1.00 | 0.600 |
| Random Effects | |||
| σ2 | 0.99 | ||
| τ00 sub | 0.10 | ||
| τ11 sub.re1.freqCond1 | 0.24 | ||
| ρ01 sub | 0.66 | ||
| ICC | 0.09 | ||
| N sub | 90 | ||
| Marginal R2 / Conditional R2 | 0.059 / 0.146 | ||
## Fitting 12 (g)lmer() models:
## [............]
## Mixed Model Anova Table (Type 3 tests, LRT-method)
##
## Model: memAcc ~ freqCond * IQScaled * (ageScaled + ageSquaredScaled) +
## Model: (freqCond | sub)
## Data: memData
## Df full model: 15
## Effect df Chisq p.value
## 1 freqCond 1 21.56 *** <.001
## 2 IQScaled 1 13.98 *** <.001
## 3 ageScaled 1 8.75 ** .003
## 4 ageSquaredScaled 1 4.37 * .037
## 5 freqCond:IQScaled 1 0.95 .331
## 6 freqCond:ageScaled 1 11.14 *** <.001
## 7 freqCond:ageSquaredScaled 1 9.62 ** .002
## 8 IQScaled:ageScaled 1 0.09 .770
## 9 IQScaled:ageSquaredScaled 1 0.03 .852
## 10 freqCond:IQScaled:ageScaled 1 2.23 .136
## 11 freqCond:IQScaled:ageSquaredScaled 1 2.58 .108
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1
| mem Acc | |||
|---|---|---|---|
| Predictors | Estimates | CI | p |
| (Intercept) | 0.27 | 0.14 – 0.39 | <0.001 |
| freqCond [1] | -0.22 | -0.30 – -0.13 | <0.001 |
| IQScaled | 0.26 | 0.13 – 0.39 | <0.001 |
| ageScaled | 1.38 | 0.49 – 2.27 | 0.002 |
| ageSquaredScaled | -0.95 | -1.84 – -0.07 | 0.034 |
| freqCond [1] * IQScaled | -0.04 | -0.14 – 0.05 | 0.329 |
| freqCond [1] * ageScaled | -1.07 | -1.69 – -0.46 | 0.001 |
|
freqCond [1] * ageSquaredScaled |
0.99 | 0.38 – 1.60 | 0.001 |
| IQScaled * ageScaled | 0.14 | -0.79 – 1.07 | 0.770 |
|
IQScaled * ageSquaredScaled |
-0.08 | -0.97 – 0.80 | 0.852 |
|
(freqCond [1] * IQScaled) * ageScaled |
-0.49 | -1.13 – 0.15 | 0.133 |
|
(freqCond [1] * IQScaled) * ageSquaredScaled |
0.51 | -0.11 – 1.12 | 0.105 |
| Random Effects | |||
| σ2 | 3.29 | ||
| τ00 sub | 0.22 | ||
| τ11 sub.freqCond1 | 0.05 | ||
| ρ01 sub | -0.27 | ||
| ICC | 0.08 | ||
| N sub | 90 | ||
| Marginal R2 / Conditional R2 | 0.079 / 0.150 | ||
## Fitting 12 (g)lmer() models:
## [............]
## Mixed Model Anova Table (Type 3 tests, LRT-method)
##
## Model: memAcc ~ freqReportScaled * (ageScaled + ageSquaredScaled) *
## Model: IQScaled + (freqReportScaled | sub)
## Data: memFreqData
## Df full model: 15
## Effect df Chisq p.value
## 1 freqReportScaled 1 32.41 *** <.001
## 2 ageScaled 1 9.23 ** .002
## 3 ageSquaredScaled 1 4.69 * .030
## 4 IQScaled 1 13.90 *** <.001
## 5 freqReportScaled:ageScaled 1 10.19 ** .001
## 6 freqReportScaled:ageSquaredScaled 1 9.51 ** .002
## 7 freqReportScaled:IQScaled 1 0.15 .698
## 8 ageScaled:IQScaled 1 0.05 .825
## 9 ageSquaredScaled:IQScaled 1 0.02 .901
## 10 freqReportScaled:ageScaled:IQScaled 1 0.85 .357
## 11 freqReportScaled:ageSquaredScaled:IQScaled 1 0.73 .394
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1
| mem Acc | |||
|---|---|---|---|
| Predictors | Estimates | CI | p |
| (Intercept) | 0.26 | 0.13 – 0.39 | <0.001 |
| freqReportScaled | 0.28 | 0.19 – 0.37 | <0.001 |
| ageScaled | 1.44 | 0.53 – 2.35 | 0.002 |
| ageSquaredScaled | -1.01 | -1.91 – -0.11 | 0.028 |
| IQScaled | 0.26 | 0.13 – 0.39 | <0.001 |
|
freqReportScaled * ageScaled |
1.11 | 0.45 – 1.77 | 0.001 |
|
freqReportScaled * ageSquaredScaled |
-1.06 | -1.72 – -0.40 | 0.002 |
|
freqReportScaled * IQScaled |
0.02 | -0.07 – 0.11 | 0.697 |
| ageScaled * IQScaled | 0.11 | -0.85 – 1.06 | 0.825 |
|
ageSquaredScaled * IQScaled |
-0.06 | -0.96 – 0.85 | 0.901 |
|
(freqReportScaled ageScaled) IQScaled |
0.33 | -0.37 – 1.04 | 0.356 |
|
(freqReportScaled ageSquaredScaled) IQScaled |
-0.29 | -0.97 – 0.38 | 0.393 |
| Random Effects | |||
| σ2 | 3.29 | ||
| τ00 sub | 0.23 | ||
| τ11 sub.re1.freqReportScaled | 0.05 | ||
| ρ01 sub | -0.14 | ||
| ICC | 0.07 | ||
| N sub | 90 | ||
| Marginal R2 / Conditional R2 | 0.089 / 0.149 | ||
## Fitting 12 (g)lmer() models:
## [............]
##
## Call:
## lm(formula = mean_pfc_scaled ~ ageScaled * IQScaled, data = mem_means)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.4400 -0.4993 -0.1544 0.4341 3.6432
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.003747 0.103171 -0.036 0.9711
## ageScaled 0.312379 0.105307 2.966 0.0039 **
## IQScaled -0.100595 0.108795 -0.925 0.3577
## ageScaled:IQScaled -0.015912 0.100431 -0.158 0.8745
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9527 on 86 degrees of freedom
## Multiple R-squared: 0.1229, Adjusted R-squared: 0.09235
## F-statistic: 4.018 on 3 and 86 DF, p-value: 0.009992
PFC activity during encoding increases with age.
##
## Call:
## lm(formula = mem_diff ~ mean_pfc_scaled * (ageScaled + ageSquaredScaled) *
## IQScaled, data = mem_means)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.45614 -0.09792 0.01422 0.12575 0.37304
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.08916 0.02322 3.840 0.000249
## mean_pfc_scaled -0.01706 0.02778 -0.614 0.540893
## ageScaled 0.46936 0.16965 2.767 0.007068
## ageSquaredScaled -0.41339 0.16720 -2.472 0.015595
## IQScaled 0.01193 0.02753 0.433 0.666070
## mean_pfc_scaled:ageScaled 0.06497 0.20251 0.321 0.749198
## mean_pfc_scaled:ageSquaredScaled -0.07122 0.19928 -0.357 0.721749
## mean_pfc_scaled:IQScaled 0.05025 0.02560 1.963 0.053181
## ageScaled:IQScaled 0.10497 0.18589 0.565 0.573918
## ageSquaredScaled:IQScaled -0.13334 0.17215 -0.775 0.440933
## mean_pfc_scaled:ageScaled:IQScaled 0.07302 0.18481 0.395 0.693853
## mean_pfc_scaled:ageSquaredScaled:IQScaled -0.06293 0.17427 -0.361 0.719010
##
## (Intercept) ***
## mean_pfc_scaled
## ageScaled **
## ageSquaredScaled *
## IQScaled
## mean_pfc_scaled:ageScaled
## mean_pfc_scaled:ageSquaredScaled
## mean_pfc_scaled:IQScaled .
## ageScaled:IQScaled
## ageSquaredScaled:IQScaled
## mean_pfc_scaled:ageScaled:IQScaled
## mean_pfc_scaled:ageSquaredScaled:IQScaled
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.1801 on 78 degrees of freedom
## Multiple R-squared: 0.24, Adjusted R-squared: 0.1329
## F-statistic: 2.24 on 11 and 78 DF, p-value: 0.02011
Overall PFC activity at encoding does not relate to memory difference scores.
##
## Call:
## lm(formula = freq_pfc_scaled ~ (ageScaled + ageSquaredScaled) *
## IQScaled, data = mem_means)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.6908 -0.4703 -0.0221 0.4317 2.3765
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.003983 0.105036 0.038 0.96984
## ageScaled 1.968308 0.742881 2.650 0.00963 **
## ageSquaredScaled -1.727762 0.734172 -2.353 0.02094 *
## IQScaled 0.255117 0.109207 2.336 0.02187 *
## ageScaled:IQScaled 0.933054 0.788859 1.183 0.24023
## ageSquaredScaled:IQScaled -1.020836 0.745112 -1.370 0.17432
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9374 on 84 degrees of freedom
## Multiple R-squared: 0.1706, Adjusted R-squared: 0.1213
## F-statistic: 3.457 on 5 and 84 DF, p-value: 0.006871
PFC activity increases non-linearly with age.
##
## Call:
## lm(formula = mem_diff_scaled ~ (ageScaled + ageSquaredScaled) +
## IQScaled, data = mem_means)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.3635 -0.4731 0.1124 0.6351 1.9283
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.655e-16 9.870e-02 0.000 1.000000
## ageScaled 2.515e+00 7.156e-01 3.514 0.000706 ***
## ageSquaredScaled -2.306e+00 7.114e-01 -3.242 0.001690 **
## IQScaled 4.205e-02 1.035e-01 0.406 0.685672
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9364 on 86 degrees of freedom
## Multiple R-squared: 0.1528, Adjusted R-squared: 0.1232
## F-statistic: 5.169 on 3 and 86 DF, p-value: 0.002479
##
## Call:
## lm(formula = freq_pfc_scaled ~ (ageScaled + ageSquaredScaled) +
## IQScaled, data = mem_means)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.59947 -0.49578 -0.02494 0.46327 2.51953
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4.802e-16 9.986e-02 0.000 1.00000
## ageScaled 2.047e+00 7.239e-01 2.828 0.00582 **
## ageSquaredScaled -1.813e+00 7.197e-01 -2.519 0.01361 *
## IQScaled 2.162e-01 1.047e-01 2.064 0.04206 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9473 on 86 degrees of freedom
## Multiple R-squared: 0.1329, Adjusted R-squared: 0.1026
## F-statistic: 4.392 on 3 and 86 DF, p-value: 0.006336
##
## Call:
## lm(formula = mem_diff_scaled ~ (ageScaled + ageSquaredScaled) +
## IQScaled + freq_pfc_scaled, data = mem_means)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.3623 -0.5731 0.1874 0.5703 1.9681
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.272e-16 9.497e-02 0.000 1.00000
## ageScaled 1.925e+00 7.198e-01 2.674 0.00898 **
## ageSquaredScaled -1.784e+00 7.094e-01 -2.515 0.01378 *
## IQScaled -2.022e-02 1.021e-01 -0.198 0.84345
## freq_pfc_scaled 2.880e-01 1.026e-01 2.809 0.00617 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.901 on 85 degrees of freedom
## Multiple R-squared: 0.2247, Adjusted R-squared: 0.1882
## F-statistic: 6.159 on 4 and 85 DF, p-value: 0.0002116
##
## Causal Mediation Analysis
##
## Nonparametric Bootstrap Confidence Intervals with the Percentile Method
##
## Estimate 95% CI Lower 95% CI Upper p-value
## ACME 0.5897 0.0832 1.36 0.018 *
## ADE 1.9250 0.5464 3.52 0.002 **
## Total Effect 2.5148 1.2772 4.09 <2e-16 ***
## Prop. Mediated 0.2345 0.0435 0.63 0.018 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Sample Size Used: 90
##
##
## Simulations: 1000
Overall, this suggests that PFC activity mediates the relation between age and memory difference scores, while controlling for IQ and quadratic age.
##
## Call:
## lm(formula = mem_diff_scaled ~ ageScaled, data = mem_means)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.09277 -0.59905 0.08106 0.55038 2.20419
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -3.017e-16 1.034e-01 0.000 1.0000
## ageScaled 2.216e-01 1.040e-01 2.131 0.0358 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9807 on 88 degrees of freedom
## Multiple R-squared: 0.04909, Adjusted R-squared: 0.03829
## F-statistic: 4.543 on 1 and 88 DF, p-value: 0.03584
##
## Call:
## lm(formula = freq_pfc_scaled ~ (ageScaled), data = mem_means)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.19130 -0.57372 -0.09097 0.53884 2.97884
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.059e-17 1.038e-01 0.000 1.0000
## ageScaled 2.009e-01 1.044e-01 1.924 0.0576 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9852 on 88 degrees of freedom
## Multiple R-squared: 0.04036, Adjusted R-squared: 0.02946
## F-statistic: 3.701 on 1 and 88 DF, p-value: 0.0576
##
## Call:
## lm(formula = mem_diff_scaled ~ ageScaled + freq_pfc_scaled, data = mem_means)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.1401 -0.5153 0.1855 0.5474 2.2187
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -3.088e-16 9.759e-02 0.000 1.000000
## ageScaled 1.526e-01 1.002e-01 1.524 0.131224
## freq_pfc_scaled 3.431e-01 1.002e-01 3.425 0.000941 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9259 on 87 degrees of freedom
## Multiple R-squared: 0.162, Adjusted R-squared: 0.1428
## F-statistic: 8.412 on 2 and 87 DF, p-value: 0.0004571
##
## Causal Mediation Analysis
##
## Nonparametric Bootstrap Confidence Intervals with the Percentile Method
##
## Estimate 95% CI Lower 95% CI Upper p-value
## ACME 0.06893 0.00793 0.15 0.018 *
## ADE 0.15264 -0.00942 0.34 0.068 .
## Total Effect 0.22157 0.04848 0.40 0.002 **
## Prop. Mediated 0.31108 0.04530 1.15 0.016 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Sample Size Used: 90
##
##
## Simulations: 1000
Yes, even without controlling for IQ and quadratic age, PFC activity mediates the relation between age and memory difference scores.
##
## Call:
## lm(formula = mem_diff_scaled ~ freq_pfc_scaled, data = mem_means)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.1637 -0.6345 0.1209 0.5906 2.1849
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -3.266e-16 9.832e-02 0.00 1.000000
## freq_pfc_scaled 3.738e-01 9.887e-02 3.78 0.000285 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9328 on 88 degrees of freedom
## Multiple R-squared: 0.1397, Adjusted R-squared: 0.1299
## F-statistic: 14.29 on 1 and 88 DF, p-value: 0.000285
##
## Call:
## lm(formula = ageScaled ~ freq_pfc_scaled, data = mem_means)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.5221 -0.8002 -0.1810 0.8057 2.0527
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -1.164e-16 1.038e-01 0.000 1.0000
## freq_pfc_scaled 2.009e-01 1.044e-01 1.924 0.0576 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9852 on 88 degrees of freedom
## Multiple R-squared: 0.04036, Adjusted R-squared: 0.02946
## F-statistic: 3.701 on 1 and 88 DF, p-value: 0.0576
##
## Call:
## lm(formula = mem_diff_scaled ~ ageScaled + freq_pfc_scaled, data = mem_means)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.1401 -0.5153 0.1855 0.5474 2.2187
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -3.088e-16 9.759e-02 0.000 1.000000
## ageScaled 1.526e-01 1.002e-01 1.524 0.131224
## freq_pfc_scaled 3.431e-01 1.002e-01 3.425 0.000941 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9259 on 87 degrees of freedom
## Multiple R-squared: 0.162, Adjusted R-squared: 0.1428
## F-statistic: 8.412 on 2 and 87 DF, p-value: 0.0004571
##
## Causal Mediation Analysis
##
## Nonparametric Bootstrap Confidence Intervals with the Percentile Method
##
## Estimate 95% CI Lower 95% CI Upper p-value
## ACME 0.03067 -0.00395 0.09 0.090 .
## ADE 0.34308 0.16572 0.54 0.002 **
## Total Effect 0.37375 0.20412 0.57 <2e-16 ***
## Prop. Mediated 0.08205 -0.01107 0.27 0.090 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Sample Size Used: 90
##
##
## Simulations: 1000
No, age does not significantly mediate the relation between PFC activity and memory difference scores.
##
## Call:
## lm(formula = freq_caudate_scaled ~ (ageScaled) * IQScaled, data = mem_means)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.7597 -0.7565 -0.1213 0.6429 2.5251
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.06833 0.10442 -0.654 0.5146
## ageScaled 0.16490 0.10658 1.547 0.1255
## IQScaled 0.18017 0.11011 1.636 0.1054
## ageScaled:IQScaled -0.29019 0.10165 -2.855 0.0054 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9642 on 86 degrees of freedom
## Multiple R-squared: 0.1016, Adjusted R-squared: 0.07023
## F-statistic: 3.241 on 3 and 86 DF, p-value: 0.02597
##
## Call:
## lm(formula = freq_caudate_scaled ~ (ageScaled + ageSquaredScaled) *
## IQScaled, data = mem_means)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.5662 -0.7761 -0.1246 0.6692 2.4036
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.09623 0.10649 -0.904 0.369
## ageScaled -0.89710 0.75320 -1.191 0.237
## ageSquaredScaled 1.07857 0.74437 1.449 0.151
## IQScaled 0.15101 0.11072 1.364 0.176
## ageScaled:IQScaled -1.23382 0.79981 -1.543 0.127
## ageSquaredScaled:IQScaled 0.91947 0.75546 1.217 0.227
##
## Residual standard error: 0.9504 on 84 degrees of freedom
## Multiple R-squared: 0.1474, Adjusted R-squared: 0.09669
## F-statistic: 2.905 on 5 and 84 DF, p-value: 0.01811
No.
##
## Call:
## lm(formula = mem_diff ~ freq_caudate_scaled * (ageScaled + ageSquaredScaled) *
## IQScaled, data = mem_means)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.44055 -0.08054 0.02601 0.09904 0.38811
##
## Coefficients:
## Estimate Std. Error t value
## (Intercept) 0.08092 0.02132 3.796
## freq_caudate_scaled 0.01287 0.02293 0.561
## ageScaled 0.50687 0.14798 3.425
## ageSquaredScaled -0.47685 0.14613 -3.263
## IQScaled 0.02063 0.02180 0.946
## freq_caudate_scaled:ageScaled 0.21480 0.15026 1.430
## freq_caudate_scaled:ageSquaredScaled -0.19396 0.14375 -1.349
## freq_caudate_scaled:IQScaled 0.02226 0.02284 0.974
## ageScaled:IQScaled 0.07313 0.17029 0.429
## ageSquaredScaled:IQScaled -0.09326 0.15873 -0.588
## freq_caudate_scaled:ageScaled:IQScaled 0.21192 0.16543 1.281
## freq_caudate_scaled:ageSquaredScaled:IQScaled -0.23098 0.15550 -1.485
## Pr(>|t|)
## (Intercept) 0.000289 ***
## freq_caudate_scaled 0.576360
## ageScaled 0.000983 ***
## ageSquaredScaled 0.001637 **
## IQScaled 0.346996
## freq_caudate_scaled:ageScaled 0.156835
## freq_caudate_scaled:ageSquaredScaled 0.181144
## freq_caudate_scaled:IQScaled 0.332862
## ageScaled:IQScaled 0.668809
## ageSquaredScaled:IQScaled 0.558525
## freq_caudate_scaled:ageScaled:IQScaled 0.203981
## freq_caudate_scaled:ageSquaredScaled:IQScaled 0.141473
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.1776 on 78 degrees of freedom
## Multiple R-squared: 0.2605, Adjusted R-squared: 0.1562
## F-statistic: 2.498 on 11 and 78 DF, p-value: 0.009606
No.
## Fitting one lmer() model. [DONE]
## Calculating p-values. [DONE]
## Fitting one lmer() model. [DONE]
## Calculating p-values. [DONE]
## Mixed Model Anova Table (Type 3 tests, S-method)
##
## Model: phc_decrease ~ IQ_scaled * (age_scaled + age_squared_scaled) +
## Model: (1 | sub)
## Data: model1_data
## Effect df F p.value
## 1 IQ_scaled 1, 80.05 0.87 .354
## 2 age_scaled 1, 79.42 3.30 + .073
## 3 age_squared_scaled 1, 79.05 4.28 * .042
## 4 IQ_scaled:age_scaled 1, 81.53 0.61 .439
## 5 IQ_scaled:age_squared_scaled 1, 80.86 0.45 .504
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1
| phc decrease | |||
|---|---|---|---|
| Predictors | Estimates | CI | p |
| (Intercept) | 44.40 | 36.66 – 52.13 | <0.001 |
| IQ_scaled | 3.83 | -4.23 – 11.90 | 0.354 |
| age_scaled | -50.67 | -105.32 – 3.98 | 0.073 |
| age_squared_scaled | 56.94 | 2.97 – 110.91 | 0.042 |
| IQ_scaled * age_scaled | 22.78 | -34.58 – 80.15 | 0.439 |
|
IQ_scaled * age_squared_scaled |
-18.53 | -72.67 – 35.61 | 0.504 |
| Random Effects | |||
| σ2 | 17188.80 | ||
| τ00 sub | 435.28 | ||
| ICC | 0.02 | ||
| N sub | 88 | ||
| Marginal R2 / Conditional R2 | 0.008 / 0.032 | ||
## Fitting one lmer() model. [DONE]
## Calculating p-values. [DONE]
## Fitting one lmer() model. [DONE]
## Calculating p-values. [DONE]
## Mixed Model Anova Table (Type 3 tests, S-method)
##
## Model: freqReport ~ phc_decrease_scaled * IQ_scaled * age_scaled + (phc_decrease_scaled ||
## Model: sub)
## Data: model2_data
## Effect df F p.value
## 1 phc_decrease_scaled 1, 1887.93 0.00 .974
## 2 IQ_scaled 1, 83.46 4.68 * .033
## 3 age_scaled 1, 83.35 8.49 ** .005
## 4 phc_decrease_scaled:IQ_scaled 1, 1893.43 0.23 .635
## 5 phc_decrease_scaled:age_scaled 1, 1892.38 2.10 .147
## 6 IQ_scaled:age_scaled 1, 83.58 1.07 .304
## 7 phc_decrease_scaled:IQ_scaled:age_scaled 1, 1896.46 0.04 .844
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1
| freq Report | |||
|---|---|---|---|
| Predictors | Estimates | CI | p |
| (Intercept) | 4.45 | 4.29 – 4.62 | <0.001 |
| phc_decrease_scaled | 0.00 | -0.06 – 0.06 | 0.974 |
| IQ_scaled | 0.19 | 0.02 – 0.36 | 0.033 |
| age_scaled | 0.25 | 0.08 – 0.42 | 0.005 |
|
phc_decrease_scaled * IQ_scaled |
0.02 | -0.05 – 0.08 | 0.635 |
|
phc_decrease_scaled * age_scaled |
0.05 | -0.02 – 0.11 | 0.147 |
| IQ_scaled * age_scaled | 0.08 | -0.08 – 0.25 | 0.304 |
|
(phc_decrease_scaled IQ_scaled) age_scaled |
0.01 | -0.05 – 0.07 | 0.844 |
| Random Effects | |||
| σ2 | 1.59 | ||
| τ00 sub | 0.51 | ||
| τ00 sub.1 | 0.00 | ||
| N sub | 88 | ||
| Marginal R2 / Conditional R2 | 0.063 / NA | ||
## Fitting 12 (g)lmer() models:
## [............]
## Mixed Model Anova Table (Type 3 tests, LRT-method)
##
## Model: memAcc ~ phc_decrease_scaled * IQ_scaled * (age_scaled + age_squared_scaled) +
## Model: (phc_decrease_scaled || sub)
## Data: model3_data
## Df full model: 14
## Effect df Chisq p.value
## 1 phc_decrease_scaled 1 10.86 *** <.001
## 2 IQ_scaled 1 15.53 *** <.001
## 3 age_scaled 1 18.60 *** <.001
## 4 age_squared_scaled 1 13.06 *** <.001
## 5 phc_decrease_scaled:IQ_scaled 1 0.01 .923
## 6 phc_decrease_scaled:age_scaled 1 0.57 .451
## 7 phc_decrease_scaled:age_squared_scaled 1 1.29 .257
## 8 IQ_scaled:age_scaled 1 1.10 .294
## 9 IQ_scaled:age_squared_scaled 1 1.28 .258
## 10 phc_decrease_scaled:IQ_scaled:age_scaled 1 0.01 .938
## 11 phc_decrease_scaled:IQ_scaled:age_squared_scaled 1 0.07 .790
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1
| mem Acc | |||
|---|---|---|---|
| Predictors | Estimates | CI | p |
| (Intercept) | 0.52 | 0.36 – 0.69 | <0.001 |
| phc_decrease_scaled | 0.21 | 0.09 – 0.33 | 0.001 |
| IQ_scaled | 0.36 | 0.19 – 0.53 | <0.001 |
| age_scaled | 2.69 | 1.52 – 3.86 | <0.001 |
| age_squared_scaled | -2.21 | -3.36 – -1.05 | <0.001 |
|
phc_decrease_scaled * IQ_scaled |
-0.01 | -0.13 – 0.12 | 0.922 |
|
phc_decrease_scaled * age_scaled |
-0.33 | -1.18 – 0.52 | 0.449 |
|
phc_decrease_scaled * age_squared_scaled |
0.51 | -0.36 – 1.37 | 0.254 |
| IQ_scaled * age_scaled | 0.65 | -0.56 – 1.86 | 0.293 |
|
IQ_scaled * age_squared_scaled |
-0.67 | -1.82 – 0.49 | 0.256 |
|
(phc_decrease_scaled IQ_scaled) age_scaled |
0.03 | -0.82 – 0.89 | 0.937 |
|
(phc_decrease_scaled IQ_scaled) age_squared_scaled |
0.11 | -0.73 – 0.96 | 0.789 |
| Random Effects | |||
| σ2 | 3.29 | ||
| τ00 sub | 0.31 | ||
| τ00 sub.1 | 0.03 | ||
| ICC | 0.09 | ||
| N sub | 88 | ||
| Marginal R2 / Conditional R2 | 0.117 / 0.193 | ||
## Fitting 24 (g)lmer() models:
## [........................]
## Mixed Model Anova Table (Type 3 tests, LRT-method)
##
## Model: memAcc ~ (age_scaled + age_squared_scaled) * IQ_scaled * phc_decrease_scaled *
## Model: freq_report_scaled + (phc_decrease_scaled * freq_report_scaled |
## Model: sub)
## Data: model4_data
## Df full model: 34
## Effect df
## 1 age_scaled 1
## 2 age_squared_scaled 1
## 3 IQ_scaled 1
## 4 phc_decrease_scaled 1
## 5 freq_report_scaled 1
## 6 age_scaled:IQ_scaled 1
## 7 age_squared_scaled:IQ_scaled 1
## 8 age_scaled:phc_decrease_scaled 1
## 9 age_squared_scaled:phc_decrease_scaled 1
## 10 IQ_scaled:phc_decrease_scaled 1
## 11 age_scaled:freq_report_scaled 1
## 12 age_squared_scaled:freq_report_scaled 1
## 13 IQ_scaled:freq_report_scaled 1
## 14 phc_decrease_scaled:freq_report_scaled 1
## 15 age_scaled:IQ_scaled:phc_decrease_scaled 1
## 16 age_squared_scaled:IQ_scaled:phc_decrease_scaled 1
## 17 age_scaled:IQ_scaled:freq_report_scaled 1
## 18 age_squared_scaled:IQ_scaled:freq_report_scaled 1
## 19 age_scaled:phc_decrease_scaled:freq_report_scaled 1
## 20 age_squared_scaled:phc_decrease_scaled:freq_report_scaled 1
## 21 IQ_scaled:phc_decrease_scaled:freq_report_scaled 1
## 22 age_scaled:IQ_scaled:phc_decrease_scaled:freq_report_scaled 1
## 23 age_squared_scaled:IQ_scaled:phc_decrease_scaled:freq_report_scaled 1
## Chisq p.value
## 1 15.61 *** <.001
## 2 11.16 *** <.001
## 3 10.65 ** .001
## 4 8.84 ** .003
## 5 23.99 *** <.001
## 6 1.51 .219
## 7 1.76 .185
## 8 0.09 .767
## 9 0.45 .504
## 10 0.00 .948
## 11 0.02 .889
## 12 0.01 .939
## 13 0.75 .386
## 14 2.77 + .096
## 15 0.00 .990
## 16 0.11 .744
## 17 0.16 .687
## 18 0.47 .495
## 19 0.12 .730
## 20 0.13 .716
## 21 0.03 .861
## 22 2.56 .110
## 23 2.74 + .098
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1
| mem Acc | |||
|---|---|---|---|
| Predictors | Estimates | CI | p |
| (Intercept) | 0.53 | 0.36 – 0.70 | <0.001 |
| age_scaled | 2.54 | 1.33 – 3.76 | <0.001 |
| age_squared_scaled | -2.11 | -3.32 – -0.91 | 0.001 |
| IQ_scaled | 0.31 | 0.13 – 0.48 | 0.001 |
| phc_decrease_scaled | 0.20 | 0.07 – 0.32 | 0.003 |
| freq_report_scaled | 0.32 | 0.20 – 0.45 | <0.001 |
| age_scaled * IQ_scaled | 0.78 | -0.46 – 2.03 | 0.218 |
|
age_squared_scaled * IQ_scaled |
-0.81 | -2.00 – 0.38 | 0.183 |
|
age_scaled * phc_decrease_scaled |
-0.13 | -1.01 – 0.74 | 0.766 |
|
age_squared_scaled * phc_decrease_scaled |
0.31 | -0.59 – 1.20 | 0.502 |
|
IQ_scaled * phc_decrease_scaled |
-0.00 | -0.14 – 0.13 | 0.947 |
|
age_scaled * freq_report_scaled |
0.06 | -0.83 – 0.96 | 0.889 |
|
age_squared_scaled * freq_report_scaled |
-0.04 | -0.94 – 0.87 | 0.939 |
|
IQ_scaled * freq_report_scaled |
-0.06 | -0.19 – 0.07 | 0.385 |
|
phc_decrease_scaled * freq_report_scaled |
-0.12 | -0.25 – 0.02 | 0.096 |
|
(age_scaled * IQ_scaled) * phc_decrease_scaled |
-0.01 | -0.90 – 0.89 | 0.990 |
|
(age_squared_scaled IQ_scaled) phc_decrease_scaled |
0.15 | -0.73 – 1.03 | 0.743 |
|
(age_scaled * IQ_scaled) * freq_report_scaled |
-0.20 | -1.18 – 0.77 | 0.686 |
|
(age_squared_scaled IQ_scaled) freq_report_scaled |
0.33 | -0.62 – 1.29 | 0.494 |
|
(age_scaled phc_decrease_scaled) freq_report_scaled |
0.16 | -0.73 – 1.04 | 0.728 |
|
(age_squared_scaled phc_decrease_scaled) freq_report_scaled |
-0.17 | -1.10 – 0.76 | 0.714 |
|
(IQ_scaled phc_decrease_scaled) freq_report_scaled |
-0.01 | -0.16 – 0.13 | 0.861 |
|
(age_scaled * IQ_scaled phc_decrease_scaled) freq_report_scaled |
-0.88 | -1.96 – 0.19 | 0.107 |
|
(age_squared_scaled IQ_scaled phc_decrease_scaled) * freq_report_scaled |
0.92 | -0.16 – 2.01 | 0.096 |
| Random Effects | |||
| σ2 | 3.29 | ||
| τ00 sub | 0.32 | ||
| τ11 sub.re1.phc_decrease_scaled | 0.02 | ||
| τ11 sub.re1.freq_report_scaled | 0.00 | ||
| τ11 sub.re1.phc_decrease_scaled_by_freq_report_scaled | 0.02 | ||
| ρ01 | -0.20 | ||
| 0.70 | |||
| -0.99 | |||
| N sub | 88 | ||
| Marginal R2 / Conditional R2 | 0.162 / NA | ||